Our research spans machine learning theory and algorithms, drawing on mathematics and statistics, such as empirical processes and numerical optimization. The vast and varied data generated in real-world domains demands advanced machine learning techniques to infer structure and extract patterns. Developing efficient, reliable, and interpretable algorithms poses significant challenges for theoreticians, ranging from learning from time-dependent data, to advancing our understanding of transfer learning and reinforcement learning, and enhancing algorithms with inference capabilities such as uncertainty quantification.

Machine learning is transforming scientific discovery, achieving state-of-the-art results across science and engineering. Our work addresses fundamental challenges in scientific machine learning and has a broad multidisciplinary component with applications spanning computational chemistry, neuroscience, robotics, and, recently, climate modeling. A particularly fruitful research direction involves the interplay between machine learning, computational physics, and numerical simulations, addressing fundamental problems such as designing physics-informed algorithms to learn dynamical systems and discovering physical laws from complex datasets.

• Arya Akhavan (University of Oxford, UK)
• Nadia Bianchi-Berthouze (University College London, UK)
• Nicolò Cesa-Bianchi (Università di Milano, Italy)
• Evgenii Chzhen (CNRS and Université Paris-Saclay, France)
• Carlo Ciliberto (University College London, UK)
• Patrick L. Combettes (North Carolina State University, USA)
• Giulia Denevi (Leonardo Labs, Italy)
• Rémi Flamary (École Polytechnique, France)
• Luca Franceschi (Amazon Berlin, Germany)
• Paolo Frasconi (Università di Firenze, Italy)
• Jordan Frecon (INRIA and Télécom Saint-Etienne, France)
• Dimitrios Giannakis (Dartmouth College, USA)
• Hélène Halconruy (Télécom SudParis, France)
• Mark Herbster (University College London, UK)
• Kara Lamb (Columbia University, USA)
• Karim Lounici (École Polytechnique, France)
• Carlos Mastalli (Heriot-Watt University, UK)
• Luca Oneto (Università di Genova, Italy)
• Patricia Reynaud-Bouret (CNRS and Université Côte d'Azur, France)
• Luca Romeo (Università di Macerata, Italy)
• Lorenzo Rosasco (Università di Genova, Italy)
• Saverio Salzo (Sapienza Università di Roma, Italy)
• Concetto Spampinato (Università di Catania, Italy)
• Alexandre Tsybakov (ENSAE Paris, France)
• Ruohan Wang (A*STAR, Singapore)
• Alain Zemkoho (University of Southampton, UK)